Cases, deaths, and testing data provided by Our World in Data on GitHub via Johns Hopkins and South Africa Department of Health. Hospitalization data from the Data Science for Social Impact Research Group @ University of Pretoria, Coronavirus COVID-19 (2019-nCoV) Data Repository for South Africa. Available on: https://github.com/dsfsi/covid19za.

I display data since the beginning of 2021. Dashed lines indicate the date (Nov 25, 2021) when the Omicron variant was announced by the South Africa National Institute for Communicable Diseases. My processing and analysis code can be found here.

Many thanks to all who have made this data available.

Cases

The line chart below shows the weekly growth multiplier of seven-day average cases. Values over 1 indicate case growth, while values under 1 mean case decline. For example, a 2.0 growth multiplier would mean cases are twice as high as the week before (rising); 0.5 would mean that they are only half as high (falling). Dots show daily values compared to seven days earlier.

Deaths

Percentage of peak values This charts display the 7-day average for deaths (black) and cases (orange) over time, expressed as the percentage of the all-time high values reached in summer 2021. Deaths are lagged by 17 days, the observed gap between the peak of cases and the peak of deaths during the summer of 2021 (Delta wave). It is designed to explore differences in disease severity over time.

Case fatality rate This chart displays the 7-day average for deaths (lagged 17 days) divided by the 7-day average for cases. The lag reflects the observed gap between the peak of cases and the peak of deaths during the summer of 2021 (Delta wave). The chart includes a loess smoothing.

Testing and Positivity

Positive rate reflects the 7-day average for new reported cases divided by the 7-day average for new reported tests. When data from JHU/Our World in Data lags reported data, I instead use figures from Data Science for Social Impact Research Group @ University of Pretoria via GitHub that include data from NICD press releases.

Hospitals

Data from Data Science for Social Impact Research Group @ University of Pretoria via GitHub. Presented first for South Africa as a whole and then for Gauteng Province specifically.

Percentage of Peak Values Case and hospitalization metrics (seven-day averages) over time as percentage of peak values for South Africa. No lags are applied. The gray area chart shows the progression of cases over time, while the lines show hospitalization metrics.

Data Table (JHU)

var date total weekday new avg_7day
cases 2021-12-06 3038075 Monday 6381 10628.00000
cases 2021-12-07 3051222 Tuesday 13147 11881.42857
cases 2021-12-08 3071064 Wednesday 19842 13493.00000
cases 2021-12-09 3093452 Thursday 22388 15043.42857
cases 2021-12-10 3112469 Friday 19017 15466.57143
cases 2021-12-11 3129622 Saturday 17153 15579.00000
cases 2021-12-12 3167497 Sunday 37875 19400.42857
cases 2021-12-13 3180785 Monday 13288 20387.14286
deaths 2021-12-06 89975 Monday 9 21.85714
deaths 2021-12-07 90002 Tuesday 27 22.71429
deaths 2021-12-08 90038 Wednesday 36 23.85714
deaths 2021-12-09 90060 Thursday 22 20.71429
deaths 2021-12-10 90080 Friday 20 19.42857
deaths 2021-12-11 90116 Saturday 36 21.57143
deaths 2021-12-12 90137 Sunday 21 24.42857
deaths 2021-12-13 90148 Monday 11 24.71429





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